Basic↦Statistic Methodology↦Study Design↦Definition
What is it? Why is it important?
A study design is an applied strategy with the aim to answer a given study question. The main and most frequently used design categories include:
- Randomized Controlled Studies (RCS): are considered the “gold standard” for assessing the effectiveness of an intervention. Participants are randomly assigned to either an intervention or a control group. Only the intervention group receives the intervention under investigation. The control group receives a reference treatment or a placebo (e.g. a treatment with no active ingredient). A causal relationship is tested by comparing the intervention with the control group
- Observational studies: are study designs where a research question is answered purely through observation. Data is collected from participants, but no attempts are made to actively intervene or affect the outcome (e.g. no treatment given). Observational studies are either prospective (e.g. data is collected prospectively) or retrospective (e.g. historical data is used for analysis)
What do I need to do?
As a SP-INV, make yourself familiar with these main study categories. Consult a statistician to discuss the most appropriate study design (within these two categories) needed to answer your study question.
Observational studies are valuable for exploring associations, identifying risk factors, and generating hypotheses. See examples of observational studies under More!
More
Example of observational studies
These studies can be either:
- Prospective: where data is collected during study conduct. Example: a group of pregnant women are followed during pregnancy while monitoring their dietary habits and their haemoglobin levels. The aim is to examine the relationship between nutrition and haemoglobin levels during pregnancy
- Retrospective: where historical data is used (e.g. patient files) of patients with a particular disease. Thus, an association between historically implemented treatments or methods (e.g. surgery procedures) and a disease status can be investigated. Example: A study analyses electronic health records from diabetic cohort patients, to investigate the association between statin use and cardiovascular outcome. The study compares the incidence of cardiovascular events between statin users and non-users over a five-year period (i.e. a cohort is a group of people with shared characteristics, such as in this example diabetes)
Where can I get help?
Your local CTU↧ can support you with experienced staff regarding this topic
Basel, Departement Klinische Forschung, CTU, dkf.unibas.ch
Lugano, Clinical Trials Unit, CTU-EOC, www.ctueoc.ch
Bern, Clinical Trials Unit, CTU, www.ctu.unibe.ch
Geneva, Clinical Research Center, CRC, crc.hug.ch
Lausanne, Clinical Research Center, CRC, www.chuv.ch
St. Gallen, Clinical Trials Unit, CTU, www.kssg.ch
Zürich, Clinical Trials Center, CTC, www.usz.ch
References
ICH Topic E9 statistical Principles for Clinical Trials – see in particular
- 2.1.1 Development plan
- 2.1.2 Confirmatory trial
- 2.1.3 Exploratory trial
- 3.1 Design configuration
Publications PubMed – see in particular
- PMID: 18313558 Erik von Elm et. al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for Reporting Observational Studies
- PMID: 20332511 David Moher et. al. CONSORT 2010 Explanation and Elaboration: Updated Guidelines for Reporting Parallel Group Randomised Trials.
Swiss Law
ClinO – see in particular article
- Art. 2b Definition of intervention